A Modified Non Linear Median Filter for the Removal of Medium Density Random Valued Impulse Noise (original) (raw)

Removal of High Density Impulse Noise using Efficient Median Filter for Digital Image

International Journal of Computer Applications, 2015

An Efficient Median Filter (EMF) algorithm for removal or enhancement of gray scale images are highly corrupted impulse noise is proposed in this paper. Noise in image are represent the pixel value 0's and 255's are ensures that black and white dot in image. In proposed algorithm take an image and select 3x3 size window and target or center pixel value check if its value is 0's or 255's then image is corrupted otherwise noise free image. If image is noisy and target pixels neighboring pixel value is between 0's and 255's then we replace pixel value with the median value and if target pixels neighboring pixel value is 0's or 255's then we replace pixel value with the mean value. Else increased the window size and again repeat this process until image is denoised. The proposed filter algorithm shows better simulation result as compare the existing algorithms. The simulation result shows better and efficient performance of PSNR and MSE and computation time.

A Modified Switching Median Filter for Reduction of Impulse Noise

This paper presents a new modified switching median filtering technique using fuzzy logic in image processing. This filter is able to remove impulse noise in digital images while preserving image details very well. The performances are compared with other filters such as median, center weighted median and traditional switching median filters for different levels of noise densities in terms of peak signal to noise ratio (PSNR). The subjective evaluations of the filters are also analyzed through various figures.

A new adaptive median filtering technique for removal of impulse noise from images

Proceedings of the 2011 International Conference on Communication, Computing & Security - ICCCS '11, 2011

This paper proposes an fuzzy based adaptive mean filtering (FBAMF) scheme to remove high density impulse noise from images. The FBAMF is a two-stage filter where, in the first stage, a fuzzy detection technique is used to differentiate between corrupted and uncorrupted pixel by calculating the membership value of each and every pixel. Then, the corrupted pixel subjected to the second stage where they are replaced by mean value of uncorrupted neighbouring pixels selected from a window adaptively. If the numbers of uncorrupted pixels in the selected window are not sufficient, a window of next higher size is chosen. Thus, window size is automatically adapted based on the density of noise in the image. As a result window size may vary pixel to pixel while filtering. Comparison shows the proposed filter effectively removes the impulse noise with significant image quality compared with conventional method such as the Standard Median Filter(SMF), Adaptive Median Filter(AMF), Progressive Switching Median Filter(PSMF) and recently proposed methods such as Efficient Decision Based Algorithm (EDBA), Improved Efficient Decision-Based Algorithm (IDBA) and fuzzy-based decision algorithm (FBDA). The visual and quantitative results show that the performance of the proposed filter in the preservation of edges and details is better even at noise level as high as 95%. The efficiency of the proposed algorithm is evaluated using different standard images.

Simple adaptive median filter for the removal of impulse noise from highly corrupted images

IEEE Transactions on Consumer Electronics, 2000

This paper presents a simple, yet efficient way to remove impulse noise from digital images. This novel method comprises two stages. The first stage is to detect the impulse noise in the image. In this stage, based on only the intensity values, the pixels are roughly divided into two classes, which are "noise-free pixel" and "noise pixel". Then, the second stage is to eliminate the impulse noise from the image. In this stage, only the "noise-pixels" are processed. The "noise-free pixels" are copied directly to the output image. The method adaptively changes the size of the median filter based on the number of the "noise-free pixels" in the neighborhood. For the filtering, only "noise-free pixels" are considered for the finding of the median value. The results from 100 test images showed that this proposed method surpasses some of the state-of-art methods, and can remove the noise from highly corrupted images, up to noise percentage of 95%. Average processing time needed to completely process images of 1600×1200 pixels with 95% noise percentage is less than 2.7 seconds. Because of its simplicity, this proposed method is suitable to be implemented in consumer electronics products such as digital television, or digital camera 1 .

Progressive switching median filter for the removal of impulse noise from highly corrupted images

IEEE Transactions on Circuits and Systems Ii: Analog and Digital Signal Processing, 1999

A new median-based filter, progressive switching median (PSM) filter, is proposed to restore images corrupted by salt-pepper impulse noise. The algorithm is developed by the following two main points: 1) switching scheme-an impulse detection algorithm is used before filtering, thus only a proportion of all the pixels will be filtered and 2) progressive methods-both the impulse detection and the noise filtering procedures are progressively applied through several iterations. Simulation results demonstrate that the proposed algorithm is better than traditional median-based filters and is particularly effective for the cases where the images are very highly corrupted.

Adaptive Window Size Median Based Filter for Impulse Noise Removal in Digital Images

International journal of engineering research and technology, 2014

In this paper, a new non-linear filter called ‘adaptive window size median based filter’ for removing salt and pepper noise and random valued impulse noise with edge and detail preservation is presented. In the proposed method, the corrupted pixels are replaced by the median value of the uncorrupted pixels in the filtering window after identifying the impulse pixel based on threshold values. Since the proposed algorithm takes a decision whether the pixel under test is corrupted or not, it works well up to a noise density as high as 70% with much lower computation time compared to the other standard techniques. Experimental results clearly indicate that the proposed method surpasses many of the existing methods such as standard median filter, weighted median filter, centre weighted median filter, recursive weighted median filter, progressive switching median filter and other proposed decision based algorithm in terms of visual quality and quantitative measures.

The Performance Analysis of Median Filter for Suppressing Impulse Noise from Images

The impulse noise suppression is a challenging task in digital image processing. In this paper, the median filtering is applied to low, medium and high detail images that are corrupted by low to high density impulse noise. The performance of a median filter is evaluated based on edge preserving capabilities, subjective and objective analysis. The simulation results indicate that the median filter preserves edges in all the categories of images.

IJERT-Nonparametric switching median filter for the removal of low level impulse noise

International Journal of Engineering Research and Technology (IJERT), 2013

https://www.ijert.org/nonparametric-switching-median-filter-for-the-removal-of-low-level-impulse-noise https://www.ijert.org/research/nonparametric-switching-median-filter-for-the-removal-of-low-level-impulse-noise-IJERTV2IS110654.pdf Most image processing applications are greatly affected by the quality of the images. However, noise is ubiquitous and often contaminates images during acquisition. In order to overcome this drawback, a new switching-based median filter technique called nonparametric switching median filter (NPSWM) is proposed for impulse noise detection and suppression in digital images. The proposed algorithm is developed based on the nonparametric framework to determine noise and noise-free pixels. In the second stage, recursive restoration technique is used to replace the detected noise pixel by the median value of the surrounding pixels. The performance of the proposed algorithm is tested and compared with some state-ofthe-art switching-based median filters existing in literature. Experimental results show that the proposed algorithm achieves superior outcomes, both in terms of subjective and objective evaluations, particularly for the cases where the images are corrupted by low level of impulse noise densities (up to 30% noise level)

Impulse Noise Detection and Removal Method Based on Modified Weighted Median

International Journal of Software Innovation

Impulse noise generally occurs because of bit errors in progression of image acquisition and transmission. It is well known that median filtering method is an impulse noise removal method. Lots of modified median filters have been proposed in the last decades to improve the methods for noise suppression and detail preservation, which have their own deficiencies while identifying and restoring noise pixels. In this article, after deeply analyzing the reasons, such as decreased noise detection and noise removal accuracy that forms the basis of the deficiencies, this article proposes a modified weighted median filter method for color images corrupted by salt-and-pepper noise. In this method, a pixel is classified into either “noise free pixel” or “noise pixel” by checking the center pixel in the current filtering window with the extreme values (0 or 255) for an 8-bit image using noise detection step. Directional differences and the number of “good” pixels in the current filtering windo...